Anne Cutler †

Publications

Displaying 1 - 13 of 13
  • Burnham, D., Ambikairajah, E., Arciuli, J., Bennamoun, M., Best, C. T., Bird, S., Butcher, A. R., Cassidy, S., Chetty, G., Cox, F. M., Cutler, A., Dale, R., Epps, J. R., Fletcher, J. M., Goecke, R., Grayden, D. B., Hajek, J. T., Ingram, J. C., Ishihara, S., Kemp, N. and 10 moreBurnham, D., Ambikairajah, E., Arciuli, J., Bennamoun, M., Best, C. T., Bird, S., Butcher, A. R., Cassidy, S., Chetty, G., Cox, F. M., Cutler, A., Dale, R., Epps, J. R., Fletcher, J. M., Goecke, R., Grayden, D. B., Hajek, J. T., Ingram, J. C., Ishihara, S., Kemp, N., Kinoshita, Y., Kuratate, T., Lewis, T. W., Loakes, D. E., Onslow, M., Powers, D. M., Rose, P., Togneri, R., Tran, D., & Wagner, M. (2009). A blueprint for a comprehensive Australian English auditory-visual speech corpus. In M. Haugh, K. Burridge, J. Mulder, & P. Peters (Eds.), Selected proceedings of the 2008 HCSNet Workshop on Designing the Australian National Corpus (pp. 96-107). Somerville, MA: Cascadilla Proceedings Project.

    Abstract

    Large auditory-visual (AV) speech corpora are the grist of modern research in speech science, but no such corpus exists for Australian English. This is unfortunate, for speech science is the brains behind speech technology and applications such as text-to-speech (TTS) synthesis, automatic speech recognition (ASR), speaker recognition and forensic identification, talking heads, and hearing prostheses. Advances in these research areas in Australia require a large corpus of Australian English. Here the authors describe a blueprint for building the Big Australian Speech Corpus (the Big ASC), a corpus of over 1,100 speakers from urban and rural Australia, including speakers of non-indigenous, indigenous, ethnocultural, and disordered forms of Australian English, each of whom would be sampled on three occasions in a range of speech tasks designed by the researchers who would be using the corpus.
  • Cutler, A., Davis, C., & Kim, J. (2009). Non-automaticity of use of orthographic knowledge in phoneme evaluation. In Proceedings of the 10th Annual Conference of the International Speech Communication Association (Interspeech 2009) (pp. 380-383). Causal Productions Pty Ltd.

    Abstract

    Two phoneme goodness rating experiments addressed the role of orthographic knowledge in the evaluation of speech sounds. Ratings for the best tokens of /s/ were higher in words spelled with S (e.g., bless) than in words where /s/ was spelled with C (e.g., voice). This difference did not appear for analogous nonwords for which every lexical neighbour had either S or C spelling (pless, floice). Models of phonemic processing incorporating obligatory influence of lexical information in phonemic processing cannot explain this dissociation; the data are consistent with models in which phonemic decisions are not subject to necessary top-down lexical influence.
  • Cutler, A. (2009). Psycholinguistics in our time. In P. Rabbitt (Ed.), Inside psychology: A science over 50 years (pp. 91-101). Oxford: Oxford University Press.
  • Cutler, A. (2001). Entries on: Acquisition of language by non-human primates; bilingualism; compound (linguistic); development of language-specific phonology; gender (linguistic); grammar; infant speech perception; language; lexicon; morphology; motor theory of speech perception; perception of second languages; phoneme; phonological store; phonology; prosody; sign language; slips of the tongue; speech perception; speech production; stress (linguistic); syntax; word recognition; words. In P. Winn (Ed.), Dictionary of biological psychology. London: Routledge.
  • Cutler, A., McQueen, J. M., Norris, D., & Somejuan, A. (2001). The roll of the silly ball. In E. Dupoux (Ed.), Language, brain and cognitive development: Essays in honor of Jacques Mehler (pp. 181-194). Cambridge, MA: MIT Press.
  • McQueen, J. M., Norris, D., & Cutler, A. (2001). Can lexical knowledge modulate prelexical representations over time? In R. Smits, J. Kingston, T. Neary, & R. Zondervan (Eds.), Proceedings of the workshop on Speech Recognition as Pattern Classification (SPRAAC) (pp. 145-150). Nijmegen: Max Planck Institute for Psycholinguistics.

    Abstract

    The results of a study on perceptual learning are reported. Dutch subjects made lexical decisions on a list of words and nonwords. Embedded in the list were either [f]- or [s]-final words in which the final fricative had been replaced by an ambiguous sound, midway between [f] and [s]. One group of listeners heard ambiguous [f]- final Dutch words like [kara?] (based on karaf, carafe) and unambiguous [s]-final words (e.g., karkas, carcase). A second group heard the reverse (e.g., ambiguous [karka?] and unambiguous karaf). After this training phase, listeners labelled ambiguous fricatives on an [f]- [s] continuum. The subjects who had heard [?] in [f]- final words categorised these fricatives as [f] reliably more often than those who had heard [?] in [s]-final words. These results suggest that speech recognition is dynamic: the system adjusts to the constraints of each particular listening situation. The lexicon can provide this adjustment process with a training signal.
  • Moore, R. K., & Cutler, A. (2001). Constraints on theories of human vs. machine recognition of speech. In R. Smits, J. Kingston, T. Neary, & R. Zondervan (Eds.), Proceedings of the workshop on Speech Recognition as Pattern Classification (SPRAAC) (pp. 145-150). Nijmegen: Max Planck Institute for Psycholinguistics.

    Abstract

    The central issues in the study of speech recognition by human listeners (HSR) and of automatic speech recognition (ASR) are clearly comparable; nevertheless the research communities that concern themselves with ASR and HSR are largely distinct. This paper compares the research objectives of the two fields, and attempts to draw informative lessons from one to the other.
  • Otake, T., & Cutler, A. (2001). Recognition of (almost) spoken words: Evidence from word play in Japanese. In P. Dalsgaard (Ed.), Proceedings of EUROSPEECH 2001 (pp. 465-468).

    Abstract

    Current models of spoken-word recognition assume automatic activation of multiple candidate words fully or partially compatible with the speech input. We propose that listeners make use of this concurrent activation in word play such as punning. Distortion in punning should ideally involve no more than a minimal contrastive deviation between two words, namely a phoneme. Moreover, we propose that this metric of similarity does not presuppose phonemic awareness on the part of the punster. We support these claims with an analysis of modern and traditional puns in Japanese (in which phonemic awareness in language users is not encouraged by alphabetic orthography). For both data sets, the results support the predictions. Punning draws on basic processes of spokenword recognition, common across languages.
  • Warner, N., Jongman, A., Mucke, D., & Cutler, A. (2001). The phonological status of schwa insertion in Dutch: An EMA study. In B. Maassen, W. Hulstijn, R. Kent, H. Peters, & P. v. Lieshout (Eds.), Speech motor control in normal and disordered speech: 4th International Speech Motor Conference (pp. 86-89). Nijmegen: Vantilt.

    Abstract

    Articulatory data are used to address the question of whether Dutch schwa insertion is a phonological or a phonetic process. By investigating tongue tip raising and dorsal lowering, we show that /l/ when it appears before inserted schwa is a light /l/, just as /l/ before an underlying schwa is, and unlike the dark /l/ before a consonant in non-insertion productions of the same words. The fact that inserted schwa can condition the light/dark /l/ alternation shows that schwa insertion involves the phonological insertion of a segment rather than phonetic adjustments to articulations.
  • Cutler, A., & Fear, B. D. (1991). Categoricality in acceptability judgements for strong versus weak vowels. In J. Llisterri (Ed.), Proceedings of the ESCA Workshop on Phonetics and Phonology of Speaking Styles (pp. 18.1-18.5). Barcelona, Catalonia: Universitat Autonoma de Barcelona.

    Abstract

    A distinction between strong and weak vowels can be drawn on the basis of vowel quality, of stress, or of both factors. An experiment was conducted in which sets of contextually matched word-intial vowels ranging from clearly strong to clearly weak were cross-spliced, and the naturalness of the resulting words was rated by listeners. The ratings showed that in general cross-spliced words were only significantly less acceptable than unspliced words when schwa was not involved; this supports a categorical distinction based on vowel quality.
  • Cutler, A. (1991). Linguistic rhythm and speech segmentation. In J. Sundberg, L. Nord, & R. Carlson (Eds.), Music, language, speech and brain (pp. 157-166). London: Macmillan.
  • Cutler, A. (1991). Prosody in situations of communication: Salience and segmentation. In Proceedings of the Twelfth International Congress of Phonetic Sciences: Vol. 1 (pp. 264-270). Aix-en-Provence: Université de Provence, Service des publications.

    Abstract

    Speakers and listeners have a shared goal: to communicate. The processes of speech perception and of speech production interact in many ways under the constraints of this communicative goal; such interaction is as characteristic of prosodic processing as of the processing of other aspects of linguistic structure. Two of the major uses of prosodic information in situations of communication are to encode salience and segmentation, and these themes unite the contributions to the symposium introduced by the present review.
  • Van Ooijen, B., Cutler, A., & Norris, D. (1991). Detection times for vowels versus consonants. In Eurospeech 91: Vol. 3 (pp. 1451-1454). Genova: Istituto Internazionale delle Comunicazioni.

    Abstract

    This paper reports two experiments with vowels and consonants as phoneme detection targets in real words. In the first experiment, two relatively distinct vowels were compared with two confusible stop consonants. Response times to the vowels were longer than to the consonants. Response times correlated negatively with target phoneme length. In the second, two relatively distinct vowels were compared with their corresponding semivowels. This time, the vowels were detected faster than the semivowels. We conclude that response time differences between vowels and stop consonants in this task may reflect differences between phoneme categories in the variability of tokens, both in the acoustic realisation of targets and in the' representation of targets by subjects.

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